SOTAVerified

Action Recognition

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

Papers

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Showing 1301–1350 of 2759 papers

TitleStatusHype
3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfaces—0
Enhanced skeleton visualization for view invariant human action recognition—0
Energy-based Periodicity Mining with Deep Features for Action Repetition Counting in Unconstrained Videos—0
Body Joint guided 3D Deep Convolutional Descriptors for Action Recognition—0
AI on the Road: A Comprehensive Analysis of Traffic Accidents and Accident Detection System in Smart Cities—0
End-to-End Spatio-Temporal Action Localisation with Video Transformers—0
End-to-End Joint Semantic Segmentation of Actors and Actions in Video—0
Action Recognition by Hierarchical Mid-level Action Elements—0
Emotion Recognition from the perspective of Activity Recognition—0
Blockwise Temporal-Spatial Pathway Network—0
Emotion-Based Crowd Representation for Abnormality Detection—0
Embedding Symbolic Temporal Knowledge into Deep Sequential Models—0
A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation—0
Else-Net: Elastic Semantic Network for Continual Action Recognition From Skeleton Data—0
ELSA: Evaluating Localization of Social Activities in Urban Streets using Open-Vocabulary Detection—0
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks—0
BlanketSet -- A clinical real-world in-bed action recognition and qualitative semi-synchronised MoCap dataset—0
A Hybrid Loss for Multiclass and Structured Prediction—0
Action Recognition based on Subdivision-Fusion Model—0
ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications—0
Elastic Functional Coding of Human Actions: From Vector-Fields to Latent Variables—0
BlanketGen2-Fit3D: Synthetic Blanket Augmentation Towards Improving Real-World In-Bed Blanket Occluded Human Pose Estimation—0
EITNet: An IoT-Enhanced Framework for Real-Time Basketball Action Recognition—0
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO—0
A Hybrid Framework for Action Recognition in Low-Quality Video Sequences—0
Eigen Evolution Pooling for Human Action Recognition—0
Binary Coding for Partial Action Analysis With Limited Observation Ratios—0
EgoViT: Pyramid Video Transformer for Egocentric Action Recognition—0
Bilinear Heterogeneous Information Machine for RGB-D Action Recognition—0
A Hierarchical Pose-Based Approach to Complex Action Understanding Using Dictionaries of Actionlets and Motion Poselets—0
Ego-Vehicle Action Recognition based on Semi-Supervised Contrastive Learning—0
Big Data and Deep Learning in Smart Cities: A Comprehensive Dataset for AI-Driven Traffic Accident Detection and Computer Vision Systems—0
EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity—0
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding—0
A Hierarchical Graph-based Approach for Recognition and Description Generation of Bimanual Actions in Videos—0
Ego-Only: Egocentric Action Detection without Exocentric Transferring—0
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation—0
Egocentric zone-aware action recognition across environments—0
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing—0
A Hierarchical Context Model for Event Recognition in Surveillance Video—0
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks—0
A Better Baseline for AVA—0
Egocentric View Hand Action Recognition by Leveraging Hand Surface and Hand Grasp Type—0
Egocentric Hand Track and Object-based Human Action Recognition—0
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness—0
A Grid-based Representation for Human Action Recognition—0
Egocentric Hand Detection Via Dynamic Region Growing—0
Egocentric Activity Recognition and Localization on a 3D Map—0
Beyond the Camera: Neural Networks in World Coordinates—0
Egocentric Action Recognition by Video Attention and Temporal Context—0
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All datasetsSomething-Something V2UCF101HMDB-51Something-Something V1AVA v2.2EPIC-KITCHENS-100NTU RGB+DNTU RGB+D 120Diving-48ActivityNetAVA v2.1H2O (2 Hands and Objects)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4—Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1—Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3—Unverified
4DejaVidTop-1 Accuracy77.2—Unverified
5InternVideoTop-1 Accuracy77.2—Unverified
6InternVideo2-1BTop-1 Accuracy77.1—Unverified
7VideoMAE V2-gTop-1 Accuracy77—Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7—Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5—Unverified
10TubeViT-LTop-1 Accuracy76.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7—Unverified
2OmniVec23-fold Accuracy99.6—Unverified
3VideoMAE V2-g3-fold Accuracy99.6—Unverified
4OmniVec3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
10LGD-3D Two-stream3-fold Accuracy98.2—Unverified